|
|
论文:2019,Vol:37,Issue(3):541-546 |
|
|
引用本文： |
|
|
苟斌, 程咏梅, 赵明艳, 王会宾, 刘成元. 三视场星敏感器的多级星图识别算法[J]. 西北工业大学学报 |
|
|
GOU Bin, CHENG Yongmei, ZHAO Mingyan, WANG Huibin, LIU Chengyuan. Multi-Stage Star Image Identification Method of Three Field-of-View Star Sensor[J]. Northwestern polytechnical university |
|
|
|
|
|
|
|
| 三视场星敏感器的多级星图识别算法 |
|
| 苟斌1, 程咏梅1, 赵明艳1, 王会宾1, 刘成元2 |
|
1. 西北工业大学 自动化学院, 陕西 西安 710129;
2. 盲信号处理国家级重点实验室, 四川 成都 610041 |
| 摘要: |
| 为解决现有三视场星图识别算法效率慢、识别正确率低的问题，提出了一种面向三视场星敏感器的多级星图识别算法：第一阶段利用单一可调参数的广义回归神经网络分别识别三幅单视场星图；第二阶段利用星库中存储的星间角距信息检验导航星识别结果，再以正确识别的导航星信息计算星敏感器的3个视轴指向；第三阶段利用视轴指向辅助未识别与识别错误的导航星完成识别与校正；最终，以三视场内正确识别的导航星精确估计飞行器姿态信息。仿真结果表明，当星点质心定位误差的标准差达到0.07像素时，该星图识别算法对实验样本的识别正确率仍高达98.9%，而识别时间仅为8.464 5 ms。同时，由于提供求解姿态的星点信息较多且分布更广泛，飞行器的三轴姿态估计精度也随之提高。三视场星敏感器估计的飞行器偏航、俯仰、和滚转轴姿态精度分别为1.205 8″，1.086 7″以及1.201 8″。 |
| 关键词:
三视场
神经网络
星图识别
姿态
|
|
| Multi-Stage Star Image Identification Method of Three Field-of-View Star Sensor |
|
| GOU Bin1, CHENG Yongmei1, ZHAO Mingyan1, WANG Huibin1, LIU Chengyuan2 |
|
1. School of Automation, Northwestern Polytechnical University, Xi'an 710129, China;
2. National Key Laboratory of Science and Technology on Blind Signal Processing, Chengdu 610041, China |
| Abstract: |
| To improve the low efficiency and low navigation star identification rate of existing star image identification methods for three field-of-view (FOV) star sensor, a multi-stage star image identification method is proposed. Firstly, the generalized regression neural network which has only one adjustable parameter, is used to identify the star images in each field-of-view. Secondly, the star angular distance saved in the navigation star database is used to verify the identification results, and then the optical directions of the three FOVs are calculated by using the correctly identified navigation stars. Thirdly, the optical directions are utilized to auxiliary correct the unidentified and erroneous identified navigation stars. Finally, the high-accuracy probe attitude is estimated by using the correctly identified navigation stars in the three FOVs. The simulation results show that the identification rates of the experimental samples is of 98.9% when the standard deviation of star centroid positioning error increases to 0.07 pixels, but the identification time is only of 8.464 5 ms. Meanwhile, since the three field-of-view star sensor captures the more dispersed navigation stars, the probe attitude accuracy of yaw, pitch and roll angles by using the present method is improved evidently, which is of 1.205 8″, 1.086 7″, and 1.201 8″, respectively. |
| Key words:
three field-of-view
neural network
star image identification
attitude
|
|
| 收稿日期: 2018-06-27
修回日期:
|
| DOI: 10.1051/jnwpu/20193730541 |
| 基金项目: 国家自然科学基金（91438107）、国家自然科学基金（61603364）与西北工业大学研究生创新基金（CX201956）资助 |
| 通讯作者:
Email： |
| 作者简介: 苟斌(1990-),西北工业大学博士研究生,主要从事天文组合导航研究。
|
|
|
|
|
|
|
|
参考文献: |
|
|
[1] 毛晓楠,梁为升,郑循江. 基于并行运算体系结构的星敏感器图像处理算法[J]. 宇航学报, 2011, 32(3):613-619 MAO Xiaonan, LIANG Weisheng, ZHENG Xunjiang. A Parallel Computing Architecture Based Image Processing Algorithm for Star Sensor[J]. Journal of Astronautics, 2011, 32(3):613-619(in Chinese)
[2] 张少迪,王延杰,孙宏海. 三角剖分以及径向基函数神经网络在星图识别中的应用[J]. 光学精密工程, 2012, 20(2):395-402 ZHANG Shaodi, WANG Yanjie, SUN Honghai. Application of Triangulation and RBF Neural Network to Star Pattern Recognition[J]. Optics & Precision Engineering, 2012, 20(2):395-402(in Chinese)
[3] 马涛,孙红辉,肖松,等. 基于BP神经网络的小样本星图识别方法[J]. 应用光学, 2009, 30(2):252-256 MA Tao, SUN Honghui, XIAO Song, et al. Recognition Algorithm for Star Pattern of Little Swatch Based on BP Neural Network[J]. Journal of Applied Optics, 2009, 30(2):252-256(in Chinese)
[4] 高社生,杨一,高兵兵. 基于渐消滤波的神经网络优化算法及其应用[J]. 西北工业大学学报, 2015, 33(2):320-325 GAO Shesheng, YANG Yi, GAO Bingbing. Neural Network Learning Algorithm Based on Fading Kalman Filtering and Its Application[J]. Journal of Northwestern Polytechnical University, 2015, 33(2):320-325(in Chinese)
[5] MIYATAKE K. Spacecraft Attitude and Body Rate Estimation with Four Star Sensor Heads:Concepts and Ground and On-Orbit Verification Results[C]//Automatic Control in Aerospace, 2010:490-494
[6] 吴量,王建立,王昊京. 三视场天文导航视场间星图识别的导航星选取[J]. 光学精密工程, 2015, 23(6):1732-1741 WU Liang, WANG Jianli, WANG Haojing. Guide Star Selection for Star Pattern Recognition between Three Fovs[J]. Optics and Precision Engineering, 2015, 23(6):1732-1741(in Chinese)
[7] 王昊京,王建立,吴量,等. 基于粗测位置和方位的三视场快速星图识别方法[J]. 中国光学, 2014, 7(5):768-778 WANG Haojing, WANG Jianli, WU Liang, et al. Fast Recognition on Star Pattern with Method of Three Fovs Based on Rough Location and Azimuth[J]. Chinese Optics, 2014, 7(5):768-778(in Chinese)
[8] 万士正,常晓飞,闫杰. 红外空空导弹气动光学传输效应分析方法[J]. 西北工业大学学报, 2015, 33(4):621-626 WAN Shizheng, CHANG Xiaofei, YAN Jie. Research Method of Aero-Optical Transmission Effect for IR Air to Air Missiles[J]. Journal of Northwestern Polytechnical University, 2015, 33(4):621-626(in Chinese)
[9] WHIPPLE F L. Smithsonian Astrophysical Observatory Star Catalog[J]. Philosophical Transactions of the Royal Society A Mathematical Physical & Engineeringences, 1966, 284(1326):431-442
[10] 杨建,张广军,江洁. P向量实现快速星图识别的方法[J]. 航空学报, 2007, 27(4):756-762 YANG Jian, ZHANG Guangjun, JIANG Jie. Fast Star Identification Algorithm Using P Vector[J]. Acta Aeronautica Et Astronautica Sinica, 2007, 28(4):897-900(in Chinese)
[11] 高晓光,邸若海,郭志高. 基于改进粒子群优化算法的贝叶斯网络结构学习[J]. 西北工业大学学报, 2014, 32(5):749-755 GAO Xiaoguang, DI Ruohai, GUO Zhigao. Bayesian Network Structure Learning Based on Improved Particle Swarm Optimization[J]. Journal of Northwestern Polytechnical University, 2014, 32(5):749-755(in Chinese)
[12] 张力军. 基于多视场星敏感器的航天器姿态确定方法研究[D]. 长沙:国防科学技术大学, 2011 ZHANG Lijun. Spacecraft Attitude Determination for Multiple Fields of View Star Sensors[D]. Changsha, National University of Defense Technology, 2011(in Chinese) |
|
|
|
|
|
|
|
